Guest instructors
Software engineer at Posit
Data science professor
University of British Columbia
Vancouver, Canada
Project lead for Futureverse
Associate professor in Epidemiology & Biostatistics
University of California
San Francisco, USA
Syllabus
We will be covering a number of topics in R programming with focus on R features helpful in bioinformatics and computational biology data analyses workflow:
- Reproducible research in R (Quarto, Rmarkdown, Renv)
- Collaborative work using Git and GitHub
- R code style guide & best practices
- Code debugging, optimization and profiling
- Parallelization and vectorization in R
- Crafting your own functions
- Object oriented programming and R classes: S3, S4, R6 and RC
- Anatomy of an R package: Creating your own package from scratch
- Tidy data flow using tidyverse
- Using the language of graphics: ggplot2
- Developing web applications using Shiny
- R and Python integration using reticulate
- Team project work - developing data analyses workflow in R using acquired skills
Course materials
Course materials will be made available at the beginning of the workshop and will remain open and publicly accessible online for at least a year. You can check out the materials from 2023.
Sessions
Our daily schedule begins with a morning session from 08:30 to 12:30, starting with breakfast from 08:30 to 09:00 and a 30-minute break at 10:30. Lunchtime is from 12:30 to 13:30. The afternoon session follows, running from 13:30 to 17:00, with a 30-minute coffee break at 15:00.
Please note that due to varying time zones, online guest lectures might occur after 17:00.
Throughout the majority of sessions, our instructors and teaching assistants will be available to aid you with practical exercises and answer any queries you may have.